GitLab

update
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Update the TF pin and see if anything breaks

* make fixup

* make fixup

* make fixup

* Document and clean more utils.

* More documentation and fixes

* Switch to Lysandre's token

* Address review comments

* Actually put else

* First draft

* Deal with progress bars

* Update src/transformers/utils/hub.py
Co-authored-by: Lucain <lucainp@gmail.com>

* Address review comments

* Forgot one

* Pin hf_hub

* Add argument for push all and fix tests

* Fix tests

* Address review comments

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Co-authored-by: Lucain <lucainp@gmail.com>

* [JAX] Bump min version

* make fixup

fix
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

fix
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Limit Pydantic to V1 in dependencies

Pydantic is about to release V2 release which will break a lot of things. This change prevents `transformers` to be used with Pydantic V2 to avoid breaking things.

* more

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* fix

* fix

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* fix

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* An end to accursed version-specific imports

* No more K.is_keras_tensor() either

* Update dependency tables

* Use a cleaner call context function getter

* Add a cap to <2.14

* Add cap to examples requirements too

* Clean up old Accelerate checks

* Put back imports

* Min accelerate

* Also min version

* Min accelerate

* Also min version

* To different minor version

* Empty

* Upgrade safetensors

* Second table

* fix for ragged list

* unpin numba

* make style

* np.object -> object

* propagate changes to tokenizer as well

* np.long -> "long"

* revert tokenization changes

* check with tokenization changes

* list/tuple logic

* catch numpy

* catch else case

* clean up

* up

* better check

* trigger ci

* Empty commit to trigger CI

* Making `safetensors` a core dependency.

To be merged later, I'm creating the PR so we can try it out.

* Update setup.py

* Remove duplicates.

* Even more redundant.

* Add a test of the built release

* Polish everything

* Trigger CI

* min. version for pytest

* fix

* fix

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Agents extras

* Add to docs

* chore: allow protobuf 3.20.3

Allow latest bugfix release for protobuf (3.20.3)

* chore: update auto-generated dependency table

update auto-generated dependency table

* run in subprocess

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Apply suggestions

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Pin optax version

* Pin flax too

* Fixup

* Use accelerate for device management

* Add accelerate to setup
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Adding Llama FastTokenizer support.

- Requires https://github.com/huggingface/tokenizers/pull/1183 version
- Only support byte_fallback for llama, raise otherwise (safety net).
- Lots of questions are special tokens

How to test:

```python

from transformers.convert_slow_tokenizer import convert_slow_tokenizer
from transformers import AutoTokenizer
from tokenizers import Tokenizer

tokenizer = AutoTokenizer.from_pretrained("huggingface/llama-7b")

if False:
    new_tokenizer = Tokenizer.from_file("tok.json")
else:
    new_tokenizer = convert_slow_tokenizer(tokenizer)
    new_tokenizer.save("tok.json")

strings = [
    "This is a test",
    "生活的真谛是",
    "生活的真谛是[MASK]。",
    # XXX: This one is problematic because of special tokens
    # "<s> Something something",
]

for string in strings:
    encoded = tokenizer(string)["input_ids"]
    encoded2 = new_tokenizer.encode(string).ids

    assert encoded == encoded2, f"{encoded} != {encoded2}"

    decoded = tokenizer.decode(encoded)
    decoded2 = new_tokenizer.decode(encoded2)

    assert decoded.strip() == decoded2, f"{repr(decoded)} != {repr(decoded2)}"
```

The converter + some test script.

The test script.

Tmp save.

Adding Fast tokenizer + tests.

Adding the tokenization tests.

Correct combination.

Small fix.

Fixing tests.

Fixing with latest update.

Rebased.

fix copies + normalized added tokens  + copies.

Adding doc.

TMP.

Doc + split files.

Doc.

Versions + try import.

Fix Camembert + warnings -> Error.

Fix by ArthurZucker.

Not a decorator.

* Fixing comments.

* Adding more to docstring.

* Doc rewriting.

* [setup] migrate setup script to `pyproject.toml`

* [setup] cleanup configurations

* remove unused imports